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All Journal Format : Jurnal Imiah Teknik Informatika TEKNOKOM : Jurnal Teknologi dan Rekayasa Sistem Komputer International Journal of Engineering Continuity International Journal of Science Education and Cultural Studies International Journal of Management Science and Application Jurnal Komputer dan Elektro Sains Jurnal Pengabdian Masyarakat Sultan Indonesia
Budi wibowo
Institut Teknologi Budi Utomo
Religion Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mechanical Engineering Social Sciences Other

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IMPLEMENTASI METODE ADASYN DALAM DETEKSI URL BERBAHAYA MENGGUNAKAN MACHINE LEARNING: DEMI MENINGKATKAN KEAMANAN SIBER DI ERA DIGITAL Gilang Dwi Setyawan; Andrie Yuswanto; Ahmad Maulid Ridwan; Budi Wibowo; Maman Firmansyah
TEKNOKOM Vol. 6 No. 2 (2023): TEKNOKOM
Publisher : Department of Computer Engineering, Universitas Wiralodra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31943/teknokom.v6i2.153

Abstract

Cybercriminals exploit malicious URLs as a distribution channel to spread harmful software across the internet. They take advantage of vulnerabilities in browsers to install malicious software with the aim of gaining remote access to the victims' computers. Typically, this malicious software aims to gain access to networks, steal sensitive information, and silently monitor targeted computer systems. In this research, a data mining approach known as Classification Based on Association (CBA) is employed to detect malicious URLs using both the URL itself and the features of the presented web pages. The CBA algorithm utilizes a training dataset of URLs as historical data to discover association rules that can be used to create an accurate classifier. By detecting dangerous URLs and malicious software, this contribution can assist organizations and individual users in enhancing the security of their computer systems and networks, thereby protecting sensitive data and reducing the risk of security incidents. The experimental results demonstrate that CBA achieves performance on par with tested classification algorithms, achieving an accuracy of 99% and low rates of false positives and false negatives. Future research could expand its focus to detect malicious URLs and software on mobile devices and embedded systems, as they have become significant targets for cybercriminals.
A Review Method for Analysis of the Causes of Data Breach in the Pasca Pandemic Yuswanto, Andrie; wibowo, Budi; Hafiz, Luqman
Jurnal Komputer dan Elektro Sains Vol. 3 No. 1 (2025): komets
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/komets.v3i1.205

Abstract

The vulnerability of personal data breaches makes countries aware of the importance of regulations governing the protection of personal data Therefore, the importance of this research is to conduct a systematic review of the causes of data breaches based on the mechanism of activities carried out to answer problems and provide solutions to problems related to information security. The Systematic Literature Review (SLR) method was used to identify 283 papers in IEEE Xplore database, direct and signature digital science library based on automated search and predefined strings. Then 18 papers were selected for study based on inclusion and exclusion criteria. From the literature study, it can be concluded that the trends analyzed, data breaches are caused by user behavior that has not been educated about the dangers of data theft and awareness of information security.
Cyber Resilience to Digital Threats for Education Institutions 4.0 Budi Wibowo; Andrie Yuswanto; Taufik Hidayat; Nadim Ibrahim
International Journal of Management Science and Application Vol. 4 No. 1 (2025): IJMSA
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijmsa.v4i1.370

Abstract

The emergence of Education 4.0, characterized by personalized learning, smart technologies, and digital interconnectivity, has revolutionized academic environments. However, this digital transformation has simultaneously increased the exposure of educational institutions to sophisticated cyber threats. This research addresses the pressing need for a robust cyber resilience framework tailored to the education sector. Employing a qualitative descriptive methodology, supported by secondary data analysis and case study reviews, the study identifies core vulnerabilities in digital infrastructure, policy shortcomings, and a general lack of cybersecurity awareness among stakeholders. In response, the paper proposes a contextualized cyber resilience framework grounded in layered security principles, zero-trust architecture, and institution-wide digital hygiene initiatives. Key findings indicate that effective cyber resilience in Education 4.0 must be multidimensional, incorporating stringent policy enforcement, continuous digital skills training, and adaptive technological strategies. The primary contribution of this study lies in offering a practical, scalable framework that aligns cybersecurity practices with the evolving demands of digital education. Future research is encouraged to explore real-time implementation metrics, cross-institutional collaborations, and the integration of AI-driven threat detection systems to further strengthen educational cyber resilience.
Enhancing Network Security and Performance using DNS Sinkhole and QoS: A Practical ISO/IEC 27001:2022 Implementation Budi Wibowo; Taufik Hidayat; Andrie Yuswanto; Aji Nurrohman
International Journal of Management Science and Application Vol. 4 No. 2 (2025): IJMSA
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijmsa.v4i2.421

Abstract

This study aims to design and validate a low-cost network security model based on open-source solutions by integrating Pi-hole and Quality of Service (QoS) as a technical implementation of ISO/IEC 27001:2022 controls for resource-constrained organizations. The implementation results demonstrate a significant improvement in security posture by blocking 14.1% of malicious and irrelevant DNS queries, while simultaneously enhancing network performance by reducing critical application latency by 45%. The key advantage of this model lies in its cost efficiency and its dual benefits of improved security and optimized performance within a single framework. However, the study also identifies limitations, particularly the potential for false positives that require manual whitelist management and reliance on trained personnel to ensure operational sustainability. The main contribution of this research is the provision of a simple, cost-effective, and standards-compliant technical framework, while also introducing a mathematical formulation to assess the trade-offs between security, performance, and cost. Future directions include integrating Intrusion Detection/Prevention Systems (IDS/IPS) for layered Defense and replicating the model into a turnkey security appliance that can be widely adopted by other organizations facing similar challenges.
An Energy-Efficient ESP32 IoT System for Real-Time Detection of WiFi Deatuhentication Attacks Faizal Riza; Dannie Febrianto Hendrakusuma; Budi Wibowo
International Journal of Engineering Continuity Vol. 4 No. 2 (2025): ijec
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijec.v4i2.433

Abstract

WiFi deauthentication attacks pose a serious threat to users on public WiFi networks by forcibly disconnecting them from access points, often as a prelude to man-in-the-middle exploits. To counter this threat, we developed an energy-efficient ESP32-based IoT system that monitors WiFi traffic in real time to identify deauthentication attack patterns. The device captures deauthentication frames in monitor mode and immediately notifies users through on-device audible/visual alarms (buzzer, LED/OLED) and digital channels (MQTT dashboard and Telegram bot). Experimental evaluation under moderate and high attack scenarios demonstrated robust performance: detection accuracy remained above 97% even under heavy attack traffic (97.8% at peak intensity). Furthermore, the system’s duty-cycled design limited average power consumption to ~79 mA (~30% lower than continuous monitoring) and achieved a rapid notification latency of ~270 ms, confirming real-time responsiveness. By combining physical indicators with online alerts, the system effectively warns users and improves public digital security literacy by making cyber threats immediately visible and understandable. Overall, these results establish the proposed system as a low-power, real-time attack detection solution that enhances WiFi network security and user awareness.
Optimalisasi Bot Telegram untuk Deteksi Situs Perjudian Online di Dunia Pendidikan dan Sektor Pemerintah Budi wibowo; Annisa Fathl Jannah; Luqman Hafiz
Jurnal Pengabdian Masyarakat Sultan Indonesia Vol. 2 No. 1 (2025): Abdisultan
Publisher : Sultan Publsiher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/abdisultan.v2i1.316

Abstract

Maraknya perjudian online telah menjadi ancaman yang signifikan terhadap keamanan digital, terutama untuk situs web pemerintah dan institusi pendidikan. Situs-situs ini, yang sering menjadi sasaran penjahat siber untuk menampung konten terkait perjudian, membuat pengguna terpapar pada berbagai risiko online. Penelitian ini menyajikan pengembangan bot Telegram yang bertujuan untuk mendeteksi situs perjudian online di situs web pemerintah dan institusi pendidikan. Bot ini menggunakan teknik dorking untuk mencari pola spesifik yang mengindikasikan konten perjudian online, memberikan peringatan waktu nyata kepada pengguna ketika situs tersebut teridentifikasi. Tujuan utama dari aplikasi ini adalah untuk meningkatkan kesadaran tentang bahaya perjudian online dan mempromosikan literasi keamanan siber, terutama di kalangan pelajar dan pengguna muda. Dengan mengirimkan notifikasi langsung ke Telegram, bot memastikan bahwa pengguna menerima pembaruan langsung tentang potensi ancaman, mendorong pendekatan proaktif terhadap keamanan online. Penelitian ini menyoroti pentingnya penggunaan teknologi untuk menjembatani kesenjangan dalam literasi digital dan menumbuhkan budaya kesadaran keamanan siber, terutama di lingkungan pendidikan. Temuan ini menunjukkan bahwa perangkat semacam itu dapat memainkan peran penting dalam mengedukasi pengguna dan melindungi mereka dari praktik-praktik online yang berbahaya, yang pada akhirnya berkontribusi pada pengembangan lingkungan internet yang lebih aman.
Social Engineering as a Major Cybersecurity Threat: Analysis of Challenges and Solutions for Organizations Budi Wibowo
International Journal of Science Education and Cultural Studies Vol. 3 No. 2 (2024): ijsecs
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijsecs.v3i2.306

Abstract

Social engineering is a psychological manipulation technique used by attackers to exploit human weaknesses in information security. This research aims to identify the challenges organizations face in protecting themselves from social engineering attacks and offer effective solutions. Through analysis of case studies and relevant literature, it was found that a lack of employee awareness and training is one of the main causes of the success of these attacks. In addition, many organizations still rely on inadequate technology to detect threats. To address these issues, this paper recommends implementing regular training programs, strengthening security policies, and using advanced technology. With this comprehensive approach, organizations can strengthen their defences and reduce the risks associated with social engineering. Organizations should prioritize continuous education programs, foster a culture cantered on security, and establish protocols that encourage alertness. Moreover, robust access controls, defined incident reporting processes, and the use of technology like behavioural analytics can further reduce the risks posed by social engineering.
Deep Learning in Wazuh Intrusion Detection System to Identify Advanced Persistent Threat (APT) Attacks Budi Wibowo; Aji Nurrohman; Luqman Hafiz
International Journal of Science Education and Cultural Studies Vol. 4 No. 1 (2025): IJSECS
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijsecs.v4i1.311

Abstract

Advanced Persistent Threats (APTs) pose a significant challenge in modern cybersecurity by leveraging persistent and sophisticated methods to compromise organizations. These threats employ advanced techniques such as encrypted communication, polymorphic malware, and log tampering, to evade detection, exfiltrate sensitive data, and disrupt critical infrastructure. Such characteristics often render conventional security measures ineffective in mitigating or preventing such attacks. This study adopted an experimental approach to assess the application of Wazuh, an advanced open-source security platform, in countering APT attacks. By simulating attack scenarios and analyzing real-time logs from diverse sources, Wazuh demonstrated strong intrusion detection capabilities, identifying attack patterns such as brute force attempts and unauthorized directory access. The findings underscore Wazuh’s effectiveness in enhancing organizational resilience by enabling rapid detection and response to suspicious activities. This research highlights how integrated log analysis can address the stealthy nature of APTs. Future studies should explore the integration of machine learning with platforms like Wazuh to further enhance automated and predictive threat detection capabilities, thereby strengthening defenses against evolving strategies of APTs.
Unveiling the Cybercrime Ecosystem: Impact of Ransomware-as-a-Service (RaaS) in Indonesia Budi wibowo; Luqman Hafiz; Taufik Hidayat
International Journal of Science Education and Cultural Studies Vol. 4 No. 1 (2025): IJSECS
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijsecs.v4i1.320

Abstract

This study explores the rise of Ransomware-as-a-Service (RaaS) in Indonesia’s cybercrime ecosystem, highlighting its role as a significant digital security threat. RaaS lowers the technical barriers to executing ransomware attacks, enabling individuals with minimal expertise to launch sophisticated cyberattacks. Analyzing data from 2020 to 2024, this study identified Indonesia as a hotspot for RaaS-driven cybercrime in Southeast Asia due to low cybersecurity awareness and weak regulatory frameworks. Key findings reveal that government administration, healthcare, and finance are the most frequently targeted sectors due to their sensitive data and inadequate defense capabilities. Ransomware variants such as Luna Moth and WannaCry, dominate the malware landscape by employing tactics like phishing and exploiting outdated systems. These attacks result in severe socioeconomic consequences, including financial losses, operational disruptions, and reputational damage. This study contributes to our understanding of RaaS by examining its operational, economic, and regulatory dimensions in the Indonesian context. This underscores the urgent need for strengthened cybersecurity policies, public-private sector collaboration, and international cooperation to address transnational cybercrime. By providing actionable insights into attack patterns and mitigation strategies, this study aims to guide efforts to combat ransomware threats and enhance Indonesia’s digital resilience.
Development of an IoT-Based Smart Waste Bin with Automated Operation and Capacity Monitoring Pria Intiadi; Gunawan Sihaloho; Al Fauzan Dito Prasetyo; Budi Wibowo
International Journal of Science Education and Cultural Studies Vol. 4 No. 2 (2025): ijsecs
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijsecs.v4i2.379

Abstract

In many public facilities, waste bins are still monitored through routine manual checks, which often results in delayed collection when the bin reaches its capacity. This situation is commonly found in campus park areas, where waste overflow reduces cleanliness and user comfort. This research aims to design and evaluate an IoT-based smart waste bin system that integrates automated lid operation and real-time capacity monitoring to improve waste management efficiency in public spaces. The system uses an ESP32 microcontroller together with an ultrasonic sensor to estimate the waste level and a Passive Infrared (PIR) sensor to detect human presence near the bin. An OLED display is included to show local system status, while remote monitoring and notifications are handled through the Blynk Console platform. The methodology involves system design, algorithm development, and simulation-based testing using the Wokwi platform. During operation, the bin lid opens when motion is detected and closes automatically after a short period. The waste level is observed continuously, and a notification is sent when the predefined capacity threshold is reached. Simulation results demonstrate an average accuracy of 98.8% for capacity detection with an absolute error of 1.2%. The system successfully performed automated lid operations, real-time status display on OLED, RGB LED status indication, and timely notifications via Blynk Console. These findings indicate that the proposed IoT-based smart waste bin can significantly enhance waste management operations in public areas by enabling proactive collection scheduling and reducing overflow incidents, thereby contributing to improved environmental hygiene and operational efficiency.
Co-Authors Abdulrahman Muhammad Abdur Rohman Ardi Agung Affan Nawly Tanjung Afuani Huyan Ahmad Maulid Ridwan Aji Nurrohman Aji Nurrohman Aji Susanto Al Fauzan Dito Prasetyo Andi Tri Setyohadi Andrie Yuswanto Andrie Yuswanto Andrie Yuswanto Annisa Fathl Jannah Annisa Fathul Jannah Dannie Febrianto Hendrakusuma Deny Danu Prasetia Fachri Alfianza Faizal Riza Febriano Anggawa Rizky Fyan Isra Wardanu Gilang Dwi Setyawan Gunawan Sihaloho Hafiz, Luqman Lela Mariya Luqman Hafiz Luqman Hafiz Mahendra Putra Maman Firmansyah Mohammad Ibrahim Mudrika Afdila Muhamad Riko Arafi Nadim Ibrahim Nida Pristyan Ramadhani Nur Afandi Pria Intiadi Qhansa Aditia Riko Adytia Anggara Santi Rahmawati Sapto Daya Hadi Saputra Sarah Azzahra Suka Hermawan Taufik Hidayat Tio Dwi Ananpasha Toto Dwi Sugiarto Yuswanto, Andrie